## Loading Data
df = read.csv("API_NY.GDP.PCAP.CD_DS2_en_csv_v2_4489299.csv", skip = 4)
## keeping only countries and columns of interest
df = df %>%
filter(Country.Name %in% c("Pakistan","India","Bangladesh"))%>%
select(-Country.Code,-Indicator.Name,-Indicator.Code)
## making horizontal data Vertical
Melted = melt(df)
## Using Country.Name, X as id variables
## cleaning Year Column
Melted$variable = gsub("X","",Melted$variable)
Melted$variable = as.numeric(Melted$variable)
## removing extra column
Melted = Melted %>%
select(-X)
## keeping data for year > 1970
Melted = Melted %>%
filter(variable >1970)
## renaming columns
names(Melted) = c("Country","Year","Value")
## function used to create data for animation
accumulate_by <- function(dat, var) {
var <- lazyeval::f_eval(var, dat)
lvls <- plotly:::getLevels(var)
dats <- lapply(seq_along(lvls), function(x) {
cbind(dat[var %in% lvls[seq(1, x)], ], frame = lvls[[x]])
})
dplyr::bind_rows(dats)
}
fig <- Melted %>% accumulate_by(~Year)
fig <- fig %>%
plot_ly(
x = ~Year,
y = ~Value,
split = ~Country,
frame = ~frame,
type = 'scatter',
mode = 'lines',
line = list(simplyfy = F)
)
fig <- fig %>% layout(
title = 'GDP Per Capita: Pakistan, India, Bangladesh',
xaxis = list(
title = "Year",
zeroline = F
),
yaxis = list(
title = "GDP Per Capita",
zeroline = F
),
legend = list(x = 0.1, y = 0.9)
)
fig <- fig %>% animation_opts(
frame = 200,
transition = 0,
redraw = FALSE
)
fig <- fig %>% animation_slider(
hide = T
)
fig <- fig %>% animation_button(
x = 1, xanchor = "right", y = 0, yanchor = "bottom"
)
fig